Structural equation modeling to detect predictors of breast self-examination behavior: Implications for intervention...

Area of Science:

• Oncology
• Public Health
• Behavioral Science

Background:

• Breast cancer is a leading malignancy in Chinese women.
• Breast self-examination (BSE) is a crucial tool for early detection and prevention.
• Identifying factors influencing BSE is vital for targeted interventions.

Purpose of the Study:

• To develop a hypothetical model identifying factors that influence breast self-examination (BSE) behavior.
• To explore the relationships between knowledge, attitudes, objective factors, and BSE in Eastern China.

Main Methods:

• Online survey administered to 1200 women aged 18-70 in Eastern China.
• Data analyzed using statistical software (IBM SPSS 25.0, AMOS 24.0).
• Structural equation modeling employed to test the hypothetical model.

Main Results:

• The model demonstrated good fit with the collected data.
• Knowledge of risk factors and positive attitudes directly and positively correlated with BSE.
• Negative attitudes showed a direct negative association with BSE.
• Objective factors directly influenced both BSE and positive attitudes, with attitudes acting as a mediator.

Conclusions:

• Knowledge of breast cancer risk factors, attitudes towards BSE, and objective factors are significant predictors of BSE behavior.
• These identified predictors can inform the development of effective breast cancer early detection programs.
• Structural equation modeling provides a robust method for understanding complex health behaviors like BSE.